Displaying publications 1 - 20 of 367 in total

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  1. The cadmium tolerance and bioaccumulation mechanism of Tetratostichococcus sp. P1: insight from transcriptomics analysis
    Sahabudin E, Kubo S, Yuzir MAM, Othman N, Nadia Md Akhir F, Suzuki K, et al.
    Bioengineered, 2024 Dec;15(1):2314888.
    PMID: 38375815 DOI: 10.1080/21655979.2024.2314888
    Cadmium (Cd) has become a severe issue in relatively low concentration and attracts expert attention due to its toxicity, accumulation, and biomagnification in living organisms. Cd does not have a biological role and causes serious health issues. Therefore, Cd pollutants should be reduced and removed from the environment. Microalgae have great potential for Cd absorption for waste treatment since they are more environmentally friendly than existing treatment methods and have strong metal sorption selectivity. This study evaluated the tolerance and ability of the microalga Tetratostichococcus sp. P1 to remove Cd ions under acidic conditions and reveal mechanisms based on transcriptomics analysis. The results showed that Tetratostichococcus sp. P1 had a high Cd tolerance that survived under the presence of Cd up to 100 µM, and IC50, the half-maximal inhibitory concentration value, was 57.0 μM, calculated from the change in growth rate based on the chlorophyll content. Long-term Cd exposure affected the algal morphology and photosynthetic pigments of the alga. Tetratostichococcus sp. P1 removed Cd with a maximum uptake of 1.55 mg g-1 dry weight. Transcriptomic analysis revealed the upregulation of the expression of genes related to metal binding, such as metallothionein. Group A, Group B transporters and glutathione, were also found upregulated. While the downregulation of the genes were related to photosynthesis, mitochondria electron transport, ABC-2 transporter, polysaccharide metabolic process, and cell division. This research is the first study on heavy metal bioremediation using Tetratostichococcus sp. P1 and provides a new potential microalga strain for heavy metal removal in wastewater.[Figure: see text]Abbreviations:BP: Biological process; bZIP: Basic Leucine Zipper; CC: Cellular component; ccc1: Ca (II)-sensitive cross complementary 1; Cd: Cadmium; CDF: Cation diffusion facilitator; Chl: Chlorophyll; CTR: Cu TRansporter families; DAGs: Directed acyclic graphs; DEGs: Differentially expressed genes; DVR: Divinyl chlorophyllide, an 8-vinyl-reductase; FPN: FerroportinN; FTIR: Fourier transform infrared; FTR: Fe TRansporter; GO: Gene Ontology; IC50: Growth half maximal inhibitory concentration; ICP: Inductively coupled plasma; MF: molecular function; NRAMPs: Natural resistance-associated aacrophage proteins; OD: Optical density; RPKM: Reads Per Kilobase of Exon Per Million Reads Mapped; VIT1: Vacuolar iron transporter 1 families; ZIPs: Zrt-, Irt-like proteins.
    Matched MeSH terms: Gene Expression Profiling
  2. Assessing the efficacy of curcumin-loaded alginate hydrogel on skin wound healing: A gene expression analysis
    Zamani S, Salehi M, Ehterami A, Fauzi MB, Abbaszadeh-Goudarzi G
    J Biomater Appl, 2024 Apr;38(9):957-974.
    PMID: 38453252 DOI: 10.1177/08853282241238581
    Skin tissue engineering has gained significant attention as a promising alternative to traditional treatments for skin injuries. In this study, we developed 3D hydrogel-based scaffolds, Alginate, incorporating different concentrations of Curcumin and evaluated their properties, including morphology, swelling behavior, weight loss, as well as hemo- and cytocompatibility. Furthermore, we investigated the therapeutic potential of Alginate hydrogel containing different amounts of Curcumin using an in vitro wound healing model. The prepared hydrogels exhibited remarkable characteristics, SEM showed that the pore size of hydrogels was 134.64 μm with interconnected pores, making it conducive for cellular infiltration and nutrient exchange. Moreover, hydrogels demonstrated excellent biodegradability, losing 63.5% of its weight over 14 days. In addition, the prepared hydrogels had a stable release of curcumin for 3 days. The results also show the hemocompatibility of prepared hydrogels and a low amount of blood clotting. To assess the efficacy of the developed hydrogels, 3T3 fibroblast growth was examined during various incubation times. The results indicated that the inclusion of Curcumin at a concentration of 0.1 mg/mL positively influenced cellular behavior. The animal study showed that Alginate hydrogel containing 0.1 mg/mL curcumin had high wound closure(more than 80%) after 14 days. In addition, it showed up-regulation of essential wound healing genes, including TGFβ1 and VEGF, promoting tissue repair and angiogenesis. Furthermore, the treated group exhibited down-regulation of MMP9 gene expression, indicating a reduction in matrix degradation and inflammation. The observed cellular responses and gene expression changes substantiate the therapeutic efficacy of prepared hydrogels. Consequently, our study showed the healing effect of alginate-based hydrogel containing Curcumin on skin injuries.
    Matched MeSH terms: Gene Expression Profiling
  3. Fulltext Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research
    Awuah WA, Roy S, Tan JK, Adebusoye FT, Qiang Z, Ferreira T, et al.
    J Cell Mol Med, 2024 Apr;28(7):e18159.
    PMID: 38494861 DOI: 10.1111/jcmm.18159
    Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.
    Matched MeSH terms: Gene Expression Profiling
  4. Comparative transcriptomics of the chilling stress response in two Asian mangrove species, Bruguiera gymnorhiza and Rhizophora apiculata
    Short AW, Sebastian JSV, Huang J, Wang G, Dassanayake M, Finnegan PM, et al.
    Tree Physiol, 2024 Feb 11;44(3).
    PMID: 38366388 DOI: 10.1093/treephys/tpae019
    Low temperatures largely determine the geographic limits of plant species by reducing survival and growth. Inter-specific differences in the geographic distribution of mangrove species have been associated with cold tolerance, with exclusively tropical species being highly cold-sensitive and subtropical species being relatively cold-tolerant. To identify species-specific adaptations to low temperatures, we compared the chilling stress response of two widespread Indo-West Pacific mangrove species from Rhizophoraceae with differing latitudinal range limits-Bruguiera gymnorhiza (L.) Lam. ex Savigny (subtropical range limit) and Rhizophora apiculata Blume (tropical range limit). For both species, we measured the maximum photochemical efficiency of photosystem II (Fv/Fm) as a proxy for the physiological condition of the plants and examined gene expression profiles during chilling at 15 and 5 °C. At 15 °C, B. gymnorhiza maintained a significantly higher Fv/Fm than R. apiculata. However, at 5 °C, both species displayed equivalent Fv/Fm values. Thus, species-specific differences in chilling tolerance were only found at 15 °C, and both species were sensitive to chilling at 5 °C. At 15 °C, B. gymnorhiza downregulated genes related to the light reactions of photosynthesis and upregulated a gene involved in cyclic electron flow regulation, whereas R. apiculata downregulated more RuBisCo-related genes. At 5 °C, both species repressed genes related to CO2 assimilation. The downregulation of genes related to light absorption and upregulation of genes related to cyclic electron flow regulation are photoprotective mechanisms that likely contributed to the greater photosystem II photochemical efficiency of B. gymnorhiza at 15 °C. The results of this study provide evidence that the distributional range limits and potentially the expansion rates of plant species are associated with differences in the regulation of photosynthesis and photoprotective mechanisms under low temperatures.
    Matched MeSH terms: Gene Expression Profiling
  5. An ensemble of bioinformatics and machine learning approaches to identify shared breast cancer biomarkers among diverse populations
    Sultan G, Zubair S
    Comput Biol Chem, 2024 Feb;108:107999.
    PMID: 38070457 DOI: 10.1016/j.compbiolchem.2023.107999
    Breast cancer continues to be a prominent cause for substantial loss of life among women globally. Despite established treatment approaches, the rising prevalence of breast cancer is a concerning trend regardless of geographical location. This highlights the need to identify common key genes and explore their biological significance across diverse populations. Our research centered on establishing a correlation between common key genes identified in breast cancer patients. While previous studies have reported many of the genes independently, our study delved into the unexplored realm of their mutual interactions, that may establish a foundational network contributing to breast cancer development. Machine learning algorithms were employed for sample classification and key gene selection. The best performance model further selected the candidate genes through expression pattern recognition. Subsequently, the genes common in all the breast cancer patients from India, China, Czech Republic, Germany, Malaysia and Saudi Arabia were selected for further study. We found that among ten classifiers, Catboost exhibited superior performance with an average accuracy of 92%. Functional enrichment analysis and pathway analysis revealed that calcium signaling pathway, regulation of actin cytoskeleton pathway and other cancer-associated pathways were highly enriched with our identified genes. Notably, we observed that these genes regulate each other, forming a complex network. Additionally, we identified PALMD gene as a novel potential biomarker for breast cancer progression. Our study revealed key gene modules forming a complex network that were consistently expressed in different populations, affirming their critical role and biological significance in breast cancer. The identified genes hold promise as prospective biomarkers of breast cancer prognosis irrespective of country of origin or ethnicity. Future investigations will expand upon these genes in a larger population and validate their biological functions through in vivo analysis.
    Matched MeSH terms: Gene Expression Profiling
  6. Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis
    Munawar WASWA, Elias MH, Addnan FH, Hassandarvish P, AbuBakar S, Roslan N
    BMC Infect Dis, 2024 Jan 23;24(1):124.
    PMID: 38263024 DOI: 10.1186/s12879-024-08983-0
    BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.

    METHODS: Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.

    RESULTS: The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.

    CONCLUSIONS: Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.

    Matched MeSH terms: Gene Expression Profiling
  7. Fulltext Genomic characterization, transcriptome analysis, and pathogenicity of the Nipah virus (Indian isolate)
    Mohandas S, Shete A, Sarkale P, Kumar A, Mote C, Yadav P
    Virulence, 2023 Dec;14(1):2224642.
    PMID: 37312405 DOI: 10.1080/21505594.2023.2224642
    Nipah virus (NiV) is a high-risk pathogen which can cause fatal infections in humans. The Indian isolate from the 2018 outbreak in the Kerala state of India showed ~ 4% nucleotide and amino acid difference in comparison to the Bangladesh strains of NiV and the substitutions observed were mostly not present in the region of any functional significance except for the phosphoprotein gene. The differential expression of viral genes was observed following infection in Vero (ATCC® CCL-81™) and BHK-21 cells. Intraperitoneal infection in the 10-12-week-old, Syrian hamster model induced dose dependant multisystemic disease characterized by prominent vascular lesions in lungs, brain, kidney and extra vascular lesions in brain and lungs. Congestion, haemorrhages, inflammatory cell infiltration, thrombosis and rarely endothelial syncitial cell formation were seen in the blood vessels. Intranasal infection resulted in respiratory tract infection characterised by pneumonia. The model showed disease characteristics resembling the human NiV infection except that of myocarditis similar to that reported by NiV-Malaysia and NiV-Bangladesh isolates in hamster model. The variation observed in the genome of the Indian isolate at the amino acid levels should be explored further for any functional significance.
    Matched MeSH terms: Gene Expression Profiling
  8. MicroRNA profiling in complete and partial hydatidiform moles
    Chia WK, Yeoh HXY, Mustangin M, Khong TY, Wong YP, Tan GC
    Malays J Pathol, 2023 Dec;45(3):353-362.
    PMID: 38155377
    INTRODUCTION: Hydatidiform mole is one of the gestational trophoblastic disease and comprises complete (CM) and partial moles (PM), which carries a risk of developing persistence disease, invasive mole or choriocarcinoma. MicroRNAs (miRNAs) have been discovered in various tissues, including neoplastic tissues. Its role in the pathogenesis of molar pregnancy or as biomarkers are still largely uncertain. The aim of this study is to identify the differentially expressed miRNAs in CM and PM.

    MATERIALS AND METHODS: Using next-generation sequencing, the miRNAs profiles of CM (n=3) and PM (n=3) moles, including placenta of non-molar abortus (n=3) as control were determined. The differentially expressed miRNAs between each group were analysed. Subsequently, bioinformatics analysis using miRDB and Targetscan was utilised to predict target genes.

    RESULTS: We found 10 differentially expressed miRNAs in CMs and PMs, compared to NMAs, namely miR- 518a-5p, miR-423-3p, miR-503-5p, miR-302a-3p, and miR-1323. The other 5 miRNAs were novel, not listed in the known database. The 3 differentially expressed miRNAs in CMs were predicted to commonly target ZTBT46 and FAM73B mRNAs.

    DISCUSSION: miR-518 was consistently observed to be downregulated in CM versus PM, and CM versus NMA. Further bioinformatic analysis to provide insight into the possible role of these miRNAs in the pathogenesis of HMs, progression of disease and as potential diagnostic biomarkers as well as therapeutic targets for HMs is needed.

    Matched MeSH terms: Gene Expression Profiling
  9. Uncovering global lipid accumulation routes towards docosahexaenoic acid (DHA) production in Aurantiochytrium sp. SW1 using integrative proteomic analysis
    Prabhakaran P, Nazir MYM, Thananusak R, Hamid AA, Vongsangnak W, Song Y
    Biochim Biophys Acta Mol Cell Biol Lipids, 2023 Nov;1868(11):159381.
    PMID: 37625782 DOI: 10.1016/j.bbalip.2023.159381
    Aurantiochytrium sp., a marine thraustochytrid possesses a remarkable ability to produce lipid rich in polyunsaturated fatty acids (PUFAs), such as docosahexaenoic acid (DHA). Although gene regulation underlying lipid biosynthesis has been previously reported, proteomic analysis is still limited. In this study, high DHA accumulating strain Aurantiochytrium sp. SW1 has been used as a study model to elucidate the alteration in proteome profile under different cultivation phases i.e. growth, nitrogen-limitation and lipid accumulation. Of the total of 5146 identified proteins, 852 proteins were differentially expressed proteins (DEPs). The largest number of DEPs (488 proteins) was found to be uniquely expressed between lipid accumulating phase and growth phase. Interestingly, there were up-regulated proteins involved in glycolysis, glycerolipid, carotenoid and glutathione metabolism which were preferable metabolic routes towards lipid accumulation and DHA production as well as cellular oxidative defence. Integrated proteomic and transcriptomic data were also conducted to comprehend the gene and protein regulation underlying the lipid and DHA biosynthesis. A significant up-regulation of acetyl-CoA synthetase was observed which suggests alternative route of acetate metabolism for acetyl-CoA producer. This study presents the holistic routes underlying lipid accumulation and DHA production in Aurantiochytrium sp. SW1 and other relevant thraustochytrid.
    Matched MeSH terms: Gene Expression Profiling
  10. Exploring the mechanisms of long COVID: Insights from computational analysis of SARS-CoV-2 gene expression and symptom associations
    Das S, Kumar S
    J Med Virol, 2023 Sep;95(9):e29077.
    PMID: 37675861 DOI: 10.1002/jmv.29077
    Long coronavirus disease (COVID) has emerged as a global health issue, affecting a substantial number of people worldwide. However, the underlying mechanisms that contribute to the persistence of symptoms in long COVID remain obscure, impeding the development of effective diagnostic and therapeutic interventions. In this study, we utilized computational methods to examine the gene expression profiles of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their associations with the wide range of symptoms observed in long COVID patients. Using a comprehensive data set comprising over 255 symptoms affecting multiple organ systems, we identified differentially expressed genes and investigated their functional similarity, leading to the identification of key genes with the potential to serve as biomarkers for long COVID. We identified the participation of hub genes associated with G-protein-coupled receptors (GPCRs), which are essential regulators of T-cell immunity and viral infection responses. Among the identified common genes were CTLA4, PTPN22, KIT, KRAS, NF1, RET, and CTNNB1, which play a crucial role in modulating T-cell immunity via GPCR and contribute to a variety of symptoms, including autoimmunity, cardiovascular disorders, dermatological manifestations, gastrointestinal complications, pulmonary impairments, reproductive and genitourinary dysfunctions, and endocrine abnormalities. GPCRs and associated genes are pivotal in immune regulation and cellular functions, and their dysregulation may contribute to the persistent immune responses, chronic inflammation, and tissue abnormalities observed in long COVID. Targeting GPCRs and their associated pathways could offer promising therapeutic strategies to manage symptoms and improve outcomes for those experiencing long COVID. However, the complex mechanisms underlying the condition require continued study to develop effective treatments. Our study has significant implications for understanding the molecular mechanisms underlying long COVID and for identifying potential therapeutic targets. In addition, we have developed a comprehensive website (https://longcovid.omicstutorials.com/) that provides a curated list of biomarker-identified genes and treatment recommendations for each specific disease, thereby facilitating informed clinical decision-making and improved patient management. Our study contributes to the understanding of this debilitating disease, paving the way for improved diagnostic precision, and individualized therapeutic interventions.
    Matched MeSH terms: Gene Expression Profiling*
  11. Unearth of small open reading frames (sORFs) in drought stress transcriptome of Oryza sativa subsp. indica
    Ong SN, Tan BC, Hanada K, Teo CH
    Gene, 2023 Aug 20;878:147579.
    PMID: 37336274 DOI: 10.1016/j.gene.2023.147579
    Drought is a major abiotic stress that influences rice production. Although the transcriptomic data of rice against drought is widely available, the regulation of small open reading frames (sORFs) in response to drought stress in rice is yet to be investigated. Different levels of drought stress have different regulatory mechanisms in plants. In this study, drought stress was imposed on four-leaf stage rice, divided into two treatments, 40% and 30% soil moisture content (SMC). The RNAs of the samples were extracted, followed by the RNA sequencing analysis on their sORF expression changes under 40%_SMC and 30%_SMC, and lastly, the expression was validated through NanoString. A total of 122 and 143 sORFs were differentially expressed (DE) in 40%_SMC and 30%_SMC, respectively. In 40%_SMC, 69 sORFs out of 696 (9%) DEGs were found to be upregulated. On the other hand, 69 sORFs out of 449 DEGs (11%) were significantly downregulated. The trend seemed to be higher in 30%_SMC, where 112 (12%) sORFs were found to be upregulated from 928 significantly upregulated DEGs. However, only 8% (31 sORFs out of 385 DEGs) sORFs were downregulated in 30%_SMC. Among the identified sORFs, 110 sORFs with high similarity to rice proteome in the PsORF database were detected in 40%_SMC, while 126 were detected in 30%_SMC. The Gene Ontology (GO) enrichment analysis of DE sORFs revealed their involvement in defense-related biological processes, such as defense response, response to biotic stimulus, and cellular homeostasis, whereas enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways indicated that DE sORFs were associated with tryptophan and phenylalanine metabolisms. Several DE sORFs were identified, including the top five sORFs (OsisORF_3394, OsisORF_0050, OsisORF_3007, OsisORF_6407, and OsisORF_7805), which have yet to be characterised. Since these sORFs were responsive to drought stress, they might hold significant potential as targets for future climate-resilient rice development.
    Matched MeSH terms: Gene Expression Profiling
  12. De Novo Transcriptomic and Life-History Responses of Moina Micrura Under Stress Environment Conditions
    Razak MR, Aris AZ, Yusoff FM, Yusof ZNB, Kim SD, Kim KW
    Mar Biotechnol (NY), 2023 Jun;25(3):473-487.
    PMID: 37310522 DOI: 10.1007/s10126-023-10220-9
    Moina micrura represents a promising model species for ecological and ecotoxicological investigations in tropical freshwater ecosystems. Illumina NovaSeq™ 6000 sequencing was employed in this study to analyze M. micrura across three distinct developmental stages: juvenile, adult, and male. Current study successfully annotated 51,547 unigenes (73.11%) derived from seven (7) different databases. A total of 554 genes were found to be significantly upregulated, while 452 genes showed significant downregulation between juvenile and male. Moreover, 1001 genes were upregulated, whereas 830 genes exhibited downregulation between the adult and male. Analysis of differentially expressed genes revealed upregulation of chitin, cuticle, myosin (MYO), mitogen-activated protein kinases (MAPK), fibrillin (FBN), cytochrome (CYP), glutathione s-transferase (GST), vitellogenin (VTG), acetylcholinesterase (AChE), and transforming growth factor beta (TGFB) under unfavorable environmental conditions (male), as compared to favorable environmental conditions (juveniles and adults). These alterations in gene expression significantly impact the phenological and life-history traits of M. micrura. Furthermore, the upregulation of hemoglobin (HMB), doublesex (DSX), juvenile hormone analogs (JHA), heat shock protein (HSP), and methyltransferase (METT) genes in males initiates the sex-switching effects observed in M. micrura. These findings hold substantial value for researchers interested in determining M. micrura sequences for future investigations of gene expression and comparative reproductive genome analysis within the Moina genus and cladoceran families.
    Matched MeSH terms: Gene Expression Profiling
  13. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network
    Huang Z, Wang J, Lu X, Mohd Zain A, Yu G
    Brief Bioinform, 2023 Mar 19;24(2).
    PMID: 36733262 DOI: 10.1093/bib/bbad040
    Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
    Matched MeSH terms: Gene Expression Profiling
  14. Fulltext Circular RNA- and microRNA-Mediated Post-Transcriptional Regulation of Preadipocyte Differentiation in Adipogenesis: From Expression Profiling to Signaling Pathway
    Huang CJ, Choo KB
    Int J Mol Sci, 2023 Feb 25;24(5).
    PMID: 36901978 DOI: 10.3390/ijms24054549
    Adipogenesis is an indispensable cellular process that involves preadipocyte differentiation into mature adipocyte. Dysregulated adipogenesis contributes to obesity, diabetes, vascular conditions and cancer-associated cachexia. This review aims to elucidate the mechanistic details on how circular RNA (circRNA) and microRNA (miRNA) modulate post-transcriptional expression of targeted mRNA and the impacted downstream signaling and biochemical pathways in adipogenesis. Twelve adipocyte circRNA profiling and comparative datasets from seven species are analyzed using bioinformatics tools and interrogations of public circRNA databases. Twenty-three circRNAs are identified in the literature that are common to two or more of the adipose tissue datasets in different species; these are novel circRNAs that have not been reported in the literature in relation to adipogenesis. Four complete circRNA-miRNA-mediated modulatory pathways are constructed via integration of experimentally validated circRNA-miRNA-mRNA interactions and the downstream signaling and biochemical pathways involved in preadipocyte differentiation via the PPARγ/C/EBPα gateway. Despite the diverse mode of modulation, bioinformatics analysis shows that the circRNA-miRNA-mRNA interacting seed sequences are conserved across species, supporting mandatory regulatory functions in adipogenesis. Understanding the diverse modes of post-transcriptional regulation of adipogenesis may contribute to the development of novel diagnostic and therapeutic strategies for adipogenesis-associated diseases and in improving meat quality in the livestock industries.
    Matched MeSH terms: Gene Expression Profiling
  15. Fulltext On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data
    Ng GYL, Tan SC, Ong CS
    PLoS One, 2023;18(10):e0292961.
    PMID: 37856458 DOI: 10.1371/journal.pone.0292961
    Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell types. Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. Generally speaking, feature selection methods are categorized into filter-, wrapper-, and embedded-based approaches. From the existing literature, methods from filter- and embedded-based approaches are widely applied in scRNA-seq gene selection tasks. The wrapper-based method that gives promising results in other fields has yet been extensively utilized for selecting gene features from scRNA-seq data; in addition, most of the existing wrapper methods used in this field are clustering instead of classification-based. With a large number of annotated data available today, this study applied a classification-based approach as an alternative to the clustering-based wrapper method. In our work, a quantum-inspired differential evolution (QDE) wrapped with a classification method was introduced to select a subset of genes from twelve well-known scRNA-seq transcriptomic datasets to identify cell types. In particular, the QDE was combined with different machine-learning (ML) classifiers namely logistic regression, decision tree, support vector machine (SVM) with linear and radial basis function kernels, as well as extreme learning machine. The linear SVM wrapped with QDE, namely QDE-SVM, was chosen by referring to the feature selection results from the experiment. QDE-SVM showed a superior cell type classification performance among QDE wrapping with other ML classifiers as well as the recent wrapper methods (i.e., FSCAM, SSD-LAHC, MA-HS, and BSF). QDE-SVM achieved an average accuracy of 0.9559, while the other wrapper methods achieved average accuracies in the range of 0.8292 to 0.8872.
    Matched MeSH terms: Gene Expression Profiling/methods
  16. Fulltext An ecological transcriptome approach to capture the molecular and physiological mechanisms of mass flowering in Shorea curtisii
    Suhaimi AH, Kobayashi MJ, Satake A, Ng CC, Lee SL, Muhammad N, et al.
    PeerJ, 2023;11:e16368.
    PMID: 38047035 DOI: 10.7717/peerj.16368
    Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation.
    Matched MeSH terms: Gene Expression Profiling
  17. Fulltext Transcriptome Profiling of the Resistance Response of Musa acuminata subsp. burmannicoides, var. Calcutta 4 to Pseudocercospora musae
    Pinheiro TDM, Rego ECS, Alves GSC, Fonseca FCA, Cotta MG, Antonino JD, et al.
    Int J Mol Sci, 2022 Nov 05;23(21).
    PMID: 36362377 DOI: 10.3390/ijms232113589
    Banana (Musa spp.), which is one of the world's most popular and most traded fruits, is highly susceptible to pests and diseases. Pseudocercospora musae, responsible for Sigatoka leaf spot disease, is a principal fungal pathogen of Musa spp., resulting in serious economic damage to cultivars in the Cavendish subgroup. The aim of this study was to characterize genetic components of the early immune response to P. musae in Musa acuminata subsp. burmannicoides, var. Calcutta 4, a resistant wild diploid. Leaf RNA samples were extracted from Calcutta 4 three days after inoculation with fungal conidiospores, with paired-end sequencing conducted in inoculated and non-inoculated controls using lllumina HiSeq 4000 technology. Following mapping to the reference M. acuminata ssp. malaccensis var. Pahang genome, differentially expressed genes (DEGs) were identified and expression representation analyzed on the basis of gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes orthology and MapMan pathway analysis. Sequence data mapped to 29,757 gene transcript models in the reference Musa genome. A total of 1073 DEGs were identified in pathogen-inoculated cDNA libraries, in comparison to non-inoculated controls, with 32% overexpressed. GO enrichment analysis revealed common assignment to terms that included chitin binding, chitinase activity, pattern binding, oxidoreductase activity and transcription factor (TF) activity. Allocation to KEGG pathways revealed DEGs associated with environmental information processing, signaling, biosynthesis of secondary metabolites, and metabolism of terpenoids and polyketides. With 144 up-regulated DEGs potentially involved in biotic stress response pathways, including genes involved in cell wall reinforcement, PTI responses, TF regulation, phytohormone signaling and secondary metabolism, data demonstrated diverse early-stage defense responses to P. musae. With increased understanding of the defense responses occurring during the incompatible interaction in resistant Calcutta 4, these data are appropriate for the development of effective disease management approaches based on genetic improvement through introgression of candidate genes in superior cultivars.
    Matched MeSH terms: Gene Expression Profiling
  18. In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
    Ealam Selvan M, Lim KS, Teo CH, Lim YY
    J Vis Exp, 2022 Oct 21.
    PMID: 36342167 DOI: 10.3791/64565
    Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via back-splicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wet-lab techniques. To solve this issue, a step-by-step protocol of in silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions.
    Matched MeSH terms: Gene Expression Profiling/methods
  19. A review on epidermal growth factor receptor's role in breast and non-small cell lung cancer
    Subramaniyan V, Fuloria S, Gupta G, Kumar DH, Sekar M, Sathasivam KV, et al.
    Chem Biol Interact, 2022 Jan 05;351:109735.
    PMID: 34742684 DOI: 10.1016/j.cbi.2021.109735
    Epithelial growth factor receptor (EGFR) is a cell surface transmembrane receptor that mediates the tyrosine signaling pathway to carry the extracellular messages inside the cell and thereby alter the function of nucleus. This leads to the generation of various protein products to up or downregulate the cellular function. It is encoded by cell erythroblastosis virus oncogene B1, so called C-erb B1/ERBB2/HER-2 gene that acts as a proto-oncogene. It belongs to the HER-2 receptor-family in breast cancer and responds best with anti-Herceptin therapy (anti-tyrosine kinase monoclonal antibody). HER-2 positive breast cancer patient exhibits worse prognosis without Herceptin therapy. Similar incidence and prognosis are reported in other epithelial neoplasms like EGFR + lung non-small cell carcinoma and glioblastoma (grade IV brain glial tumor). Present study highlights the role and connectivity of EGF with various cancers via signaling pathways, cell surface receptors mechanism, macromolecules, mitochondrial genes and neoplasm. Present study describes the EGFR associated gene expression profiling (in breast cancer and NSCLC), relation between mitrochondrial genes and carcinoma, and several in vitro and in vivo models to screen the synergistic effect of various combination treatments. According to this study, although clinical studies including targeted treatments, immunotherapies, radiotherapy, TKi-EGFR combined targeted therapy have been carried out to investigate the synergism of combination therapy; however still there is a gap to apply the scenarios of experimental and clinical studies for further developments. This review will give an idea about the transition from experimental to most advanced clinical studies with different combination drug strategies to treat cancer.
    Matched MeSH terms: Gene Expression Profiling
  20. Fulltext Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication
    Dirong G, Nematbakhsh S, Selamat J, Chong PP, Idris LH, Nordin N, et al.
    Molecules, 2021 Oct 28;26(21).
    PMID: 34770913 DOI: 10.3390/molecules26216502
    Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.
    Matched MeSH terms: Gene Expression Profiling
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